{"id":108989,"date":"2026-09-23T05:09:04","date_gmt":"2026-09-22T21:09:04","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/108989.html"},"modified":"2026-09-23T05:09:04","modified_gmt":"2026-09-22T21:09:04","slug":"mindspore-lite-%e7%ab%af%e4%be%a7%e6%8e%a8%e7%90%86%e7%9a%84-tensor%e3%80%81%e5%8a%a8%e6%80%81-shape-%e4%b8%8e%e5%bc%82%e6%9e%84%e6%89%a7%e8%a1%8c%e9%93%be%e3%80%90%e9%b8%bf%e8%92%99%e5%bf%83%e8%bf%b9","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/108989.html","title":{"rendered":"MindSpore Lite \u7aef\u4fa7\u63a8\u7406\u7684 Tensor\u3001\u52a8\u6001 Shape \u4e0e\u5f02\u6784\u6267\u884c\u94fe\u3010\u9e3f\u8499\u5fc3\u8ff9\u3011"},"content":{"rendered":"

\u540c\u4e00\u4e2a\u6a21\u578b，\u4e3a\u4ec0\u4e48\u5f00\u53d1\u673a\u8dd1 20ms，\u653e\u5230\u624b\u673a\u4e0a\u5c31\u53d8\u6210 100ms？<\/p>\n

\"\u6587\u7ae0\u5c01\u9762\"<\/p>\n

\u505a\u7aef\u4fa7 AI \u7684\u65f6\u5019，\u6700\u5f00\u59cb\u7684\u601d\u8def\u5f88\u7b80\u5355：\u6a21\u578b\u6587\u4ef6\u62ff\u8fc7\u6765，\u52a0\u8f7d\u4e86，Predict \u4e00\u4e0b\u4e0d\u5c31\u884c\u4e86？<\/p>\n

\u7ed3\u679c\u771f\u653e\u5230\u624b\u673a\u4e0a\u8dd1，\u53d1\u73b0\u4e0d\u5bf9：\u5f00\u53d1\u673a\u4e0a 20ms \u7684\u6a21\u578b，\u624b\u673a\u4e0a\u8dd1\u4e86 100ms\u3002\u751a\u81f3\u6709\u7684\u6a21\u578b\u76f4\u63a5\u8dd1\u4e0d\u8d77\u6765\u3002<\/p>\n

\u8fd9\u65f6\u5019\u624d\u610f\u8bc6\u5230：\u7aef\u4fa7\u63a8\u7406\u4e0d\u662f"\u628a\u6a21\u578b\u6587\u4ef6\u52a0\u8f7d\u4e86\u5c31\u5b8c\u4e8b"\u3002\u6a21\u578b\u6587\u4ef6\u53ea\u662f\u4e2a\u9759\u6001\u6587\u4ef6，\u771f\u6b63\u8dd1\u8d77\u6765\u7684\u65f6\u5019，\u6709\u4e00\u5927\u5806\u4e1c\u897f\u8981\u5904\u7406：\u5185\u5b58\u3001Shape\u3001\u7b97\u5b50\u8c03\u5ea6\u3001\u5f02\u6784\u6267\u884c\u3002<\/p>\n

\u4e00\u3001\u5148\u60f3\u6e05\u695a：Predict() \u5230\u5e95\u505a\u4e86\u4ec0\u4e48<\/h3>\n

\u5148\u770b\u4e00\u6bb5\u6700\u666e\u901a\u7684\u63a8\u7406\u4ee3\u7801：<\/p>\n

OH_AI_Model *<\/span>model;<\/span>
\nOH_AI_Tensor *<\/span>input;<\/span>
\nOH_AI_Tensor *<\/span>output;<\/span><\/p>\n

OH_AI_ModelPredict<\/span>(<\/span>model,<\/span> &<\/span>input,<\/span> 1<\/span>,<\/span> &<\/span>output,<\/span> 1<\/span>)<\/span>;<\/span><\/p>\n

\u8fd9\u4e00\u884c\u8c03\u7528，\u770b\u8d77\u6765\u5c31\u662f\u8dd1\u4e00\u6b21\u63a8\u7406\u3002\u4f46\u5b9e\u9645\u4e0a，\u8fd9\u4e00\u884c\u80cc\u540e\u505a\u4e86\u591a\u5c11\u4e8b？<\/p>\n\n\u9636\u6bb5\u505a\u4ec0\u4e48<\/tr>\n\n\n\n\n\n\n\n
\u6a21\u578b\u52a0\u8f7d<\/td>\n\u4ece\u6587\u4ef6\u8bfb\u6a21\u578b，\u89e3\u6790\u7ed3\u6784<\/td>\n<\/tr>\n
Model Build<\/td>\n\u628a\u6a21\u578b\u7f16\u8bd1\u6210\u53ef\u6267\u884c\u56fe<\/td>\n<\/tr>\n
Tensor \u51c6\u5907<\/td>\n\u5206\u914d\u8f93\u5165\u8f93\u51fa\u5185\u5b58<\/td>\n<\/tr>\n
Shape \u68c0\u67e5<\/td>\n\u786e\u8ba4\u8f93\u5165 Shape \u5bf9\u4e0d\u5bf9<\/td>\n<\/tr>\n
\u7b97\u5b50\u6267\u884c<\/td>\n\u6bcf\u4e2a\u7b97\u5b50\u5728 CPU\/NPU \u4e0a\u8dd1<\/td>\n<\/tr>\n
\u7ed3\u679c\u8f93\u51fa<\/td>\n\u4ece Tensor \u62ff\u7ed3\u679c<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u8fd9\u4e00\u884c Predict()，\u80cc\u540e\u662f\u4e00\u6574\u5957\u6267\u884c\u5f15\u64ce\u5728\u8dd1\u3002<\/p>\n

\u4e8c\u3001\u6a21\u578b\u6587\u4ef6\u548c\u53ef\u6267\u884c\u6a21\u578b\u6709\u4ec0\u4e48\u533a\u522b<\/h3>\n

\u5f88\u591a\u4eba\u4ee5\u4e3a：\u6a21\u578b\u6587\u4ef6\u52a0\u8f7d\u4e86，\u5c31\u80fd\u76f4\u63a5\u8dd1\u3002\u4e0d\u5bf9\u3002<\/p>\n

\u6a21\u578b\u6587\u4ef6\u662f\u9759\u6001\u7684，\u5b58\u7740\u7b97\u5b50\u7ed3\u6784\u3001\u6743\u91cd\u8fd9\u4e9b\u4fe1\u606f\u3002\u4f46\u5b83\u8fd8\u4e0d\u80fd\u76f4\u63a5\u5728 CPU\/NPU \u4e0a\u8dd1\u3002<\/p>\n

\u8981\u5148 Build：\u628a\u6a21\u578b\u6587\u4ef6\u7f16\u8bd1\u6210\u5f53\u524d\u786c\u4ef6\u53ef\u6267\u884c\u7684\u683c\u5f0f\u3002<\/p>\n\n\u6982\u5ff5\u662f\u4ec0\u4e48<\/tr>\n\n\n\n
\u6a21\u578b\u6587\u4ef6<\/td>\n\u9759\u6001\u6587\u4ef6，\u5b58\u7b97\u5b50\u548c\u6743\u91cd<\/td>\n<\/tr>\n
Build \u540e\u7684\u6a21\u578b<\/td>\n\u53ef\u6267\u884c\u7684，\u8dd1\u5728\u5f53\u524d\u786c\u4ef6\u4e0a<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Build \u4e0d\u662f\u77ac\u95f4\u5b8c\u6210\u7684，\u5b83\u8981\u505a\u5f88\u591a\u4f18\u5316：\u7b97\u5b50\u878d\u5408\u3001\u5185\u5b58\u89c4\u5212\u3001\u5f02\u6784\u8c03\u5ea6\u3002Build \u4e00\u6b21，\u4e4b\u540e\u6bcf\u6b21\u63a8\u7406\u5c31\u5feb\u4e86\u3002<\/p>\n

\u8fd9\u6bb5\u4ee3\u7801\u89e3\u51b3\u4ec0\u4e48\u95ee\u9898： \u52a0\u8f7d\u5e76 Build \u6a21\u578b\u3002
\n\u6587\u4ef6： ai\/InferenceEngine.cpp
\n\u7528\u9014： \u7aef\u4fa7\u6a21\u578b\u63a8\u7406
\n\u63a5\u5165\u4f4d\u7f6e： AI \u63a8\u7406\u6a21\u5757\u521d\u59cb\u5316<\/p>\n

\/\/ \u521b\u5efa Context<\/span>
\nOH_AI_Context *<\/span>context =<\/span> OH_AI_ContextCreate<\/span>(<\/span>)<\/span>;<\/span><\/p>\n

\/\/ \u8bbe\u7f6e\u7ebf\u7a0b\u6570\u548c\u7ed1\u6838<\/span>
\nOH_AI_ContextSetThreadNum<\/span>(<\/span>context,<\/span> 4<\/span>)<\/span>;<\/span>
\nOH_AI_ContextSetThreadAffinity<\/span>(<\/span>context,<\/span> true<\/span>)<\/span>;<\/span><\/p>\n

\/\/ \u521b\u5efa Model<\/span>
\nOH_AI_Model *<\/span>model =<\/span> OH_AI_ModelCreate<\/span>(<\/span>)<\/span>;<\/span><\/p>\n

\/\/ Build：\u4ece\u6587\u4ef6\u52a0\u8f7d\u5e76\u7f16\u8bd1<\/span>
\nOH_AI_Status status =<\/span> OH_AI_ModelBuildFromFile<\/span>(<\/span>
\n model,<\/span>
\n "model.ms"<\/span>,<\/span>
\n OH_AI_MODEL_TYPE_MINDIR,<\/span>
\n context
\n)<\/span>;<\/span><\/p>\n

\u8fd9\u91cc\u6700\u5173\u952e\u7684\u662f Build\u3002Build \u662f\u91cd\u64cd\u4f5c，\u4e0d\u80fd\u6bcf\u6b21\u63a8\u7406\u90fd\u91cd\u65b0 Build\u3002<\/p>\n

\"\u7cfb\u7edf\u67b6\u6784\u56fe\"<\/p>\n

\u4e09\u3001Tensor \u548c Shape \u4e3a\u4ec0\u4e48\u8fd9\u4e48\u91cd\u8981<\/h3>\n

\u6a21\u578b\u8dd1\u8d77\u6765，\u6570\u636e\u600e\u4e48\u4f20\u8fdb\u53bb？\u901a\u8fc7 Tensor\u3002<\/p>\n

Tensor \u6709 Shape，\u4e5f\u5c31\u662f\u5b83\u7684\u7ef4\u5ea6\u3002\u6bd4\u5982\u4e00\u4e2a\u56fe\u7247 Tensor，Shape \u662f [1, 3, 224, 224]：1 \u5f20\u56fe，3 \u901a\u9053，224\u00d7224\u3002<\/p>\n

\u8f93\u5165 Shape \u53d8\u4e86，\u6bd4\u5982\u4ece 224\u00d7224 \u53d8\u6210 640\u00d7640，\u4f1a\u53d1\u751f\u4ec0\u4e48？<\/p>\n\n\u60c5\u51b5\u8981\u4e0d\u8981\u91cd\u65b0\u5904\u7406<\/tr>\n\n\n\n
Shape \u4e0d\u53d8<\/td>\n\u76f4\u63a5\u63a8\u7406<\/td>\n<\/tr>\n
Shape \u53d8\u4e86<\/td>\n\u8981 Resize<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Resize \u662f\u4ec0\u4e48？\u5c31\u662f\u91cd\u65b0\u89c4\u5212\u5185\u5b58，\u91cd\u65b0\u505a\u6267\u884c\u56fe\u4f18\u5316\u3002\u56e0\u4e3a Shape \u53d8\u4e86，\u5185\u5b58\u9700\u6c42\u53d8\u4e86，\u7b97\u5b50\u8c03\u5ea6\u4e5f\u53ef\u80fd\u53d8\u3002<\/p>\n

\u56db\u3001\u52a8\u6001 Shape \u662f\u4ec0\u4e48<\/h3>\n

\u9759\u6001 Shape：\u6a21\u578b\u7684\u8f93\u5165\u5927\u5c0f\u662f\u56fa\u5b9a\u7684，\u6bd4\u5982\u5fc5\u987b\u662f 224\u00d7224\u3002<\/p>\n

\u52a8\u6001 Shape：\u6a21\u578b\u7684\u8f93\u5165\u5927\u5c0f\u662f\u53ef\u53d8\u7684，\u6bd4\u5982\u53ef\u4ee5\u5728 [1, 3, 224, 224] \u5230 [1, 3, 640, 640] \u4e4b\u95f4\u53d8\u3002<\/p>\n

\u52a8\u6001 Shape \u5f88\u7075\u6d3b，\u4f46\u4e5f\u6709\u4ee3\u4ef7：<\/p>\n\n\u7c7b\u578b\u5185\u5b58\u5360\u7528\u7075\u6d3b\u6027<\/tr>\n\n\n\n
\u9759\u6001 Shape<\/td>\n\u5c0f，\u53ea\u6309\u56fa\u5b9a\u5927\u5c0f\u5206\u914d<\/td>\n\u4e0d\u7075\u6d3b<\/td>\n<\/tr>\n
\u52a8\u6001 Shape<\/td>\n\u5927，\u6309\u6700\u5927\u53ef\u80fd\u5206\u914d<\/td>\n\u7075\u6d3b<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u52a8\u6001 Shape \u7684\u8303\u56f4\u4e0d\u80fd\u8bbe\u8ba1\u592a\u5927\u3002\u8303\u56f4\u592a\u5927\u4e86，\u5185\u5b58\u6309\u6700\u5927\u7684\u5206\u914d，\u6d6a\u8d39\u5f88\u591a\u3002<\/p>\n

\u4e94\u3001CPU \u548c NPU \u5f02\u6784\u6267\u884c\u662f\u4ec0\u4e48\u610f\u601d<\/h3>\n

\u5f88\u591a\u4eba\u4ee5\u4e3a：\u914d\u7f6e\u4e86 NPU，\u6240\u6709\u7b97\u5b50\u90fd\u5728 NPU \u4e0a\u8dd1\u3002\u4e0d\u5bf9\u3002<\/p>\n

NPU \u4e0d\u662f\u4e07\u80fd\u7684\u3002\u6709\u4e9b\u7b97\u5b50 NPU \u4e0d\u652f\u6301，\u5c31\u4f1a\u56de\u9000\u5230 CPU \u8dd1\u3002\u8fd9\u53eb CPU Fallback\u3002<\/p>\n\n\u7b97\u5b50\u7c7b\u578b\u5728\u54ea\u91cc\u8dd1<\/tr>\n\n\n\n
NPU \u652f\u6301\u7684<\/td>\nNPU \u8dd1，\u5feb<\/td>\n<\/tr>\n
NPU \u4e0d\u652f\u6301\u7684<\/td>\nCPU \u8dd1，\u6162<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u6240\u4ee5\u5373\u4f7f\u914d\u7f6e\u4e86 NPU，\u6a21\u578b\u91cc\u6709\u7b97\u5b50 NPU \u4e0d\u652f\u6301，\u90a3\u90e8\u5206\u8fd8\u662f\u5728 CPU \u4e0a\u8dd1，\u6574\u4f53\u901f\u5ea6\u5c31\u4e0a\u4e0d\u53bb\u3002<\/p>\n

\u8fd9\u6bb5\u4ee3\u7801\u89e3\u51b3\u4ec0\u4e48\u95ee\u9898： \u6267\u884c\u63a8\u7406\u3002
\n\u6587\u4ef6： ai\/InferenceEngine.cpp
\n\u7528\u9014： \u4e00\u6b21\u6a21\u578b\u63a8\u7406
\n\u63a5\u5165\u4f4d\u7f6e： \u6bcf\u6b21\u9884\u6d4b\u8c03\u7528<\/p>\n

\/\/ \u83b7\u53d6\u8f93\u5165 Tensor<\/span>
\nOH_AI_Tensor *<\/span>input =<\/span> OH_AI_ModelGetInputTensorByTensorName<\/span>(<\/span>model,<\/span> "input"<\/span>)<\/span>;<\/span><\/p>\n

\/\/ \u8bbe\u7f6e\u8f93\u5165 Shape<\/span>
\nOH_AI_TensorSetDataType<\/span>(<\/span>input,<\/span> OH_AI_DATATYPE_FLOAT32)<\/span>;<\/span>
\nOH_AI_TensorSetShape<\/span>(<\/span>input,<\/span> {<\/span>1<\/span>,<\/span> 3<\/span>,<\/span> 224<\/span>,<\/span> 224<\/span>}<\/span>)<\/span>;<\/span><\/p>\n

\/\/ \u628a\u6570\u636e\u62f7\u8d1d\u5230 Tensor<\/span>
\nOH_AI_TensorCopyFromBuffer<\/span>(<\/span>input,<\/span> inputData,<\/span> inputSize)<\/span>;<\/span><\/p>\n

\/\/ \u6267\u884c\u63a8\u7406<\/span>
\nOH_AI_ModelPredict<\/span>(<\/span>model,<\/span> &<\/span>input,<\/span> 1<\/span>,<\/span> &<\/span>output,<\/span> 1<\/span>)<\/span>;<\/span><\/p>\n

\/\/ \u4ece\u8f93\u51fa Tensor \u62ff\u7ed3\u679c<\/span>
\nOH_AI_TensorCopyToBuffer<\/span>(<\/span>output,<\/span> outputData,<\/span> outputSize)<\/span>;<\/span><\/p>\n

\"\u8fd0\u884c\u6548\u679c\u56fe\"<\/p>\n

\u516d\u3001\u51e0\u4e2a\u5bb9\u6613\u8e29\u7684\u5751<\/h3>\n

\u7b2c\u4e00\u4e2a\u5751：\u6a21\u578b Build \u6bcf\u6b21\u63a8\u7406\u90fd\u91cd\u65b0\u6267\u884c\u3002Build \u662f\u91cd\u64cd\u4f5c，\u4e00\u6b21\u5c31\u591f\u4e86\u3002<\/p>\n

\u7b2c\u4e8c\u4e2a\u5751：Context \u91cd\u590d\u590d\u7528\u5230\u591a\u4e2a Model Build\u3002Context \u662f\u4e00\u6b21\u6027\u7684，\u6bcf\u4e2a\u6a21\u578b\u5355\u72ec\u5efa\u3002<\/p>\n

\u7b2c\u4e09\u4e2a\u5751：\u8f93\u5165 Shape \u6539\u53d8\u5374\u4e0d Resize\u3002Shape \u53d8\u4e86\u5185\u5b58\u5c31\u4e0d\u5bf9\u4e86\u3002<\/p>\n

\u7b2c\u56db\u4e2a\u5751：\u4ee5\u4e3a\u914d\u7f6e NPU \u540e\u6240\u6709\u7b97\u5b50\u90fd\u4f1a\u8dd1 NPU\u3002\u4e0d\u652f\u6301\u7684\u7b97\u5b50\u56de\u9000 CPU\u3002<\/p>\n

\u7b2c\u4e94\u4e2a\u5751：Tensor Buffer \u751f\u547d\u5468\u671f\u6bd4 Predict \u77ed\u3002Tensor \u8fd8\u5728\u7528，Buffer \u5df2\u7ecf\u91ca\u653e\u4e86\u3002<\/p>\n

\u7b2c\u516d\u4e2a\u5751：\u76f2\u76ee\u589e\u52a0\u63a8\u7406\u7ebf\u7a0b\u6570\u3002\u7ebf\u7a0b\u592a\u591a\u53cd\u800c\u6162，\u8fd8\u6709\u4e0a\u4e0b\u6587\u5207\u6362\u5f00\u9500\u3002<\/p>\n

\u7b2c\u4e03\u4e2a\u5751：\u52a8\u6001 Shape \u8303\u56f4\u8bbe\u8ba1\u8fc7\u5927\u3002\u5185\u5b58\u6d6a\u8d39\u5f88\u591a\u3002<\/p>\n

\u7b2c\u516b\u4e2a\u5751：\u53ea\u770b\u6a21\u578b\u6587\u4ef6\u5927\u5c0f\u5224\u65ad\u8fd0\u884c\u65f6\u5185\u5b58\u3002\u6a21\u578b\u6587\u4ef6\u5c0f，\u8fd0\u884c\u65f6\u5185\u5b58\u53ef\u80fd\u5f88\u5927\u3002<\/p>\n

\u4e03\u3001\u4e3a\u4ec0\u4e48\u5f00\u53d1\u673a\u548c\u624b\u673a\u5dee\u8fd9\u4e48\u591a<\/h3>\n

\u5f00\u53d1\u673a\u8dd1 20ms，\u624b\u673a\u8dd1 100ms，\u5dee\u5728\u54ea\u91cc？<\/p>\n\n\u56e0\u7d20\u5f00\u53d1\u673a\u624b\u673a<\/tr>\n\n\n\n\n\n
CPU \u6027\u80fd<\/td>\n\u5f3a<\/td>\n\u5f31<\/td>\n<\/tr>\n
NPU \u52a0\u901f<\/td>\n\u6709<\/td>\n\u6709，\u4f46\u7b97\u5b50\u652f\u6301\u4e0d\u5168<\/td>\n<\/tr>\n
\u5185\u5b58\u5e26\u5bbd<\/td>\n\u5927<\/td>\n\u5c0f<\/td>\n<\/tr>\n
\u6563\u70ed<\/td>\n\u597d<\/td>\n\u5dee，\u5bb9\u6613\u964d\u9891<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

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